Darlington, T. | Search bioRxiv

bioRxiv2017

Genome-wide association study of suicide death:Results from the first wave of Utah completed suicide data

ObjectiveSuicide death is a highly preventable, yet growing, worldwide health crisis. To date, there has been a lack of adequately powered genomic studies of suicide, with no sizeable suicide death cohorts available for study. To address this limitation, we conducted the first comprehensive genomic analysis of suicide death, using a previously unpublished suicide cohort. MethodsThe analysis sample consisted of 3,413 population-ascertained cases of European ancestry and 14,810 ancestrally matched controls. Analytical methods included principle components analysis for ancestral matching and adjusting for population stratification, linear mixed model genome-wide association testing (conditional on genetic relatedness matrix), gene and gene set enrichment testing, polygenic score analyses, as well as SNP heritability and genetic correlation estimation using LD score regression. ResultsGWAS identified two genome-wide significant loci (6 SNPs, p<5x10-8). Gene-based analyses implicated 19 genes on chromosomes 13, 15, 16, 17, and 19 (q<0.05). Suicide heritability was estimated h2 =0.2463, SE = 0.0356 using summary statistics from a multivariate logistic GWAS adjusting for ancestry. Notably, suicide polygenic scores were robustly predictive of out of sample suicide death, as were polygenic scores for several other psychiatric disorders and psychological traits, particularly behavioral disinhibition and major depressive disorder. ConclusionsIn this report, we identify multiple genome-wide significant loci/genes, and demonstrate robust polygenic score prediction of suicide death case-control status, adjusting for ancestry, in independent training and test sets. Additionally, we report that suicide death cases have increased genetic risk for behavioral disinhibition, major depression, autism spectrum disorder, psychosis, and alcohol use disorder relative to controls. Results demonstrate the ability of polygenic scores to robustly, and multidimensionally, predict suicide death case-control status.

genomics↗

bioRxiv2017

High-risk Autism Spectrum Disorder Utah pedigrees: a novel Shared Genomic Segments analysis.

Progress in gene discovery for Autism Spectrum Disorder (ASD) has been rapid over the past decade, with major successes in validation of risk of predominantly rare, penetrant, de novo and inherited mutations in over 100 genes (de Rubies et al., 2015; Sanders et al., 2015). However, the majority of individuals with ASD diagnoses do not carry a rare, penetrant genetic risk factor. In fact, recent estimates suggest that most of the genetic liability of ASD is due to as yet undiscovered common, less penetrant inherited variation (Gaugler et al., 2014) which is much more difficult to detect. The study of extended, high-risk families adds significant information in our search for these common inherited risk factors. Here, we present results of a new, powerful pedigree analysis method (Shared Genomic Segments--SGS) on three large families from the Utah Autism Research Program. The method improves upon previous methods by allowing for within-family heterogeneity, and identifying exact region boundaries and subsets of cases who share for targeted follow-up analyses. Our SGS analyses identified one genome-wide significant shared segment on chromosome 17 (q21.32, p=1.47x10-8). Additional regions with suggestive evidence were identified on chromosomes 3, 4, 6, 8, 11, 13, 14, 15, and 18. Several of these segments showed evidence of sharing across families. Genes of interest in these regions include ATP8A1, DOCK3, CACNA2D2, ITGB3, AMBRA1, FOLH1, DGKZ, MTHFS, ARNT2, BTN2A2, BTN3A1, BTN3A3, BTN2A1, and BTN1A1. We are exploring multiple other lines of evidence to follow up these implicated regions and genes.

genetics↗